# May 2, 2026

## Daily

### DeepSeek V4–almost on the frontier, a fraction of the price

- **DeepSeek V4** introduces two models, **DeepSeek-V4-Pro** and **DeepSeek-V4-Flash**, featuring **1 million token context Mixture of Experts**, with Pro boasting **1.6T total parameters** and Flash at **284B total parameters**.

### LLMs consistently pick resumes they generate over ones by humans or other models

- **LLMs exhibit a significant self-preference bias**, favoring their own generated resumes over human-written ones, with a bias range of **67% to 82%** across various models, even when controlling for content quality.

### Eka’s robotic claw feels like we're approaching a ChatGPT moment

- **Eka's robotic claw demonstrates unprecedented dexterity**, capable of tasks like screwing in light bulbs and handling delicate items, suggesting a potential **ChatGPT moment for robotics** in the physical realm.

### Uber wants to turn its drivers into a sensor grid for self-driving companies

- **Uber aims to transform its millions of drivers into a vast sensor grid**, collecting real-world data for autonomous vehicle (AV) companies, thereby addressing the critical data bottleneck in AV development.

### I spent years building a 103B-token Usenet corpus (1980–2013) and finally documented it

- The **Usenet corpus** comprises **103.1 billion tokens** and **408 million posts**, offering a rich dataset for language model training that spans **33 years** of online discourse from **1980 to 2013**.

### LFM2-24B-A2B: Scaling Up the LFM2 Architecture

- **LFM2-24B-A2B** is a **sparse Mixture of Experts (MoE)** model with **24 billion parameters**, demonstrating effective scaling and consistent quality improvements across benchmarks as it expands from **350M to 24B** parameters.

### Real World Physics-Informed AI Applications

- **Physics-informed AI** integrates physical laws into machine learning models, enhancing their predictive capabilities in real-world scenarios, such as engineering and environmental science.